Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector ...

Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to fit our model to the data set. Gradient Descent finds the minima of cost function ...

But in practice, a model is usually trained using iterative stochastic gradient ... the Main() method in the Program class. The Program class also holds helper functions to load data from file into ...

For example, sorting algorithms turn unordered data into data ordered by some criteria, often the numeric or alphabetical order of one or more fields in the data. Linear regression algorithms fit ...

The assumption of linear regression is that the objective function is linearly correlated ... typically use some form of gradient descent algorithm to drive the back propagation, often with ...

MIT CSAIL and Meta researchers present a novel technique that enables gradient descent optimizers such as SGD and Adam to tune their hyperparameters automatically. The method requires no manual ...